CVE-2022-36019
published 2022-09-16CVE-2022-36019: TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVarsPerChannel` is given `min` or `max` tensors of a rank other than one, it…
PriorityP337high7.5CVSS 3.1
AVNACLPRNUINSUCNINAH
EPSS
0.41%
33.3th percentile
TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVarsPerChannel` is given `min` or `max` tensors of a rank other than one, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Affected
11 ranges
| Vendor | Product | Version range | Fixed in |
|---|---|---|---|
| debian | tensorflow | — | — |
| tensorflow | < 2.7.2 | 2.7.2 | |
| tensorflow | — | — | |
| tensorflow | >= 2.8.0 < 2.8.1 | 2.8.1 | |
| tensorflow | >= 2.9.0 < 2.9.1 | 2.9.1 | |
| intel | optimization_for_tensorflow | >= 0 < 2.7.2 | 2.7.2 |
| intel | optimization_for_tensorflow | >= 2.8.0 < 2.8.1 | 2.8.1 |
| intel | optimization_for_tensorflow | >= 2.9.0 < 2.9.1 | 2.9.1 |
| tensorflow | tensorflow | < 2.7.2 | 2.7.2 |
| tensorflow | tensorflow | — | — |
| tensorflow | tensorflow | — | — |
CVSS provenance
nvdv3.17.5HIGHCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
vendor_debian5.9LOW
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OSV
TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannel`
osv·2022-09-16
CVE-2022-36019 [MEDIUM] TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannel`
TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannel`
### Impact
If `FakeQuantWithMinMaxVarsPerChannel` is given `min` or `max` tensors of a rank other than one, it results in a `CHECK` fail that can be used to trigger a denial of service attack.
```python
import tensorflow as tf
num_bits = 8
narrow_range = False
inputs = tf.constant(0, shape=[4], dtype=tf.float32)
min = tf.constant([], shape=[4,0,0], dtype=tf.float32)
max = tf.constant(0, shape=[4], dtype=tf.float32)
tf.raw_ops.FakeQuantWithMinMaxVarsPerChannel(inputs=inputs, min=min, max=max, num_bits=num_bits, narrow_range=narrow_range)
```
### Patches
We have patched the issue in GitHub commit [785d67a78a1d533759fcd2f5e8d6ef778de849e0](https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d
GHSA
TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannel`
ghsa·2022-09-16
CVE-2022-36019 [MEDIUM] CWE-617 TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannel`
TensorFlow vulnerable to `CHECK` fail in `FakeQuantWithMinMaxVarsPerChannel`
### Impact
If `FakeQuantWithMinMaxVarsPerChannel` is given `min` or `max` tensors of a rank other than one, it results in a `CHECK` fail that can be used to trigger a denial of service attack.
```python
import tensorflow as tf
num_bits = 8
narrow_range = False
inputs = tf.constant(0, shape=[4], dtype=tf.float32)
min = tf.constant([], shape=[4,0,0], dtype=tf.float32)
max = tf.constant(0, shape=[4], dtype=tf.float32)
tf.raw_ops.FakeQuantWithMinMaxVarsPerChannel(inputs=inputs, min=min, max=max, num_bits=num_bits, narrow_range=narrow_range)
```
### Patches
We have patched the issue in GitHub commit [785d67a78a1d533759fcd2f5e8d6ef778de849e0](https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d
Debian
CVE-2022-36019: tensorflow - TensorFlow is an open source platform for machine learning. If `FakeQuantWithMin...
vendor_debian·2022·CVSS 5.9
CVE-2022-36019 [MEDIUM] CVE-2022-36019: tensorflow - TensorFlow is an open source platform for machine learning. If `FakeQuantWithMin...
TensorFlow is an open source platform for machine learning. If `FakeQuantWithMinMaxVarsPerChannel` is given `min` or `max` tensors of a rank other than one, it results in a `CHECK` fail that can be used to trigger a denial of service attack. We have patched the issue in GitHub commit 785d67a78a1d533759fcd2f5e8d6ef778de849e0. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.
Scope: local
forky: resolved
sid: resolved
No detection rules found.
No public exploits indexed.
No writeups or analysis indexed.
https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9j4v-pp28-mxv7https://github.com/tensorflow/tensorflow/commit/785d67a78a1d533759fcd2f5e8d6ef778de849e0https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9j4v-pp28-mxv7
2022-09-16
Published